Reverse Osmosis/Nanofiltration/Ultrafiltration (RO/NF/UF) is a pressure driven membrane separation process used in various industries such as desalination, wastewater treatment and chemical manufacturing. RO/NF/UF is used in plants to produce potable water from sea/brackish water. In an RO/NF/UF process, high pressure is applied on the feed side of the membrane to overcome the osmotic pressure of solute and cause transport of the solvent from the feed side to a permeate side and solute accumulates near the membrane surface. As a result, the concentration of the solute near the membrane surface increases gradually over a period, adversely affecting the performance of membrane. This phenomena is called concentration polarization. The concentration polarization is inversely proportional to the feed velocity across the membrane module. As recovery increases, the flow velocity across the membrane decreases, causing increased concentration polarization. Product recovery depends on other variables like feed concentration, pressure and temperature. In RO/NF/UF plants, the membrane fouling rate due to concentration polarization is influenced by multiple factors such as changes in feed concentration, temperature, and pressure, and it is difficult for the plant operator to determine the root cause for a changing fouling rate in a RO/NF/UF plant. Prediction of the changes in the fouling rate would help the plant operators in taking maintenance actions like cleaning the membrane to restore the performance to a desired level.
In industry, cleaning of the membrane is carried out in at least two ways; either based on a pressure drop between the feed and reject being more than a threshold value, or at predetermined fixed periodic intervals as per a recommendation by a membrane manufacturer. In the first method, the membrane may get damaged due to permanent fouling, and in the second method, membrane cleaning is independent of the actual fouling taking place in the membrane modules. Thus, both these methods of membrane cleaning are not satisfactory since the fouling rate changes with time and is dependent on the feed flow rate, concentration, pressure and temperature.
Different methods have been reported in literature for online cleaning and performance monitoring of a membrane separation process. Ooe Kenji and Okada Shingo [28] reported online method for performance analysis of an RO plant based on an ASTM D-4516 [1] method. The ASTM D-4516 method does not allow for discovering the development of membrane fouling or scaling until it results in significant loss of product quality such as product flow, and salt passage. In addition, this technique is applicable only where the plant is operated as per the design conditions and capacity with recovery being equal to or less than 15%.
Mohamad Amin Saad [16] extended the ASTM method to measure “Fouling Monitor” (FM) to monitor the performance of an RO plant. The FM is defined as a percentage difference between the normalized flux at design conditions and actual flux at the operating conditions of the RO plant. A cleaning scheduling of a membrane is arrived at based on the value of the FM. This method cannot predict the fouling of the membrane based on the operating conditions before normalized flux deviates from a design value. In addition, the method based on normalized flux may not be sufficient to predict fouling of a membrane accurately.
Nalco chemical company [18-27] has developed a method for monitoring the performance of a membrane separation process. As per the method, a tracer is injected in the feed stream and the concentration of tracer in outlet streams was estimated experimentally by using external sensors. The tracer concentrations in the feed and the outlet streams are used to monitor the fouling taking place in the membrane separation processes. This technique involves external sensors and tracer injection systems for implementation.
University Technology Corporation [U.S. Pat. No. 6,161,435] has developed a method and apparatus for monitoring membrane modules by using an ultrasonic sound technique. Due to fouling, the membrane thickness increases from the original value. Cleaning of the membrane is scheduled based on the monitoring of the membrane thickness using an ultrasonic technique. This method involves an individual ultrasonic transducer to monitor fouling at each membrane module.
The methods described above are not based on actual plant operating conditions and do not account for any time varying nature of fouling taking place in the membrane units.
Several mathematical models dealing with solute transfer in a membrane separation process have been reported in literature. Broadly, these membrane transport models may be divided in two categories (i) for neutral (reverse osmosis) membranes and (ii) for charged (nanofiltration and charged reverse osmosis) membranes. The mathematical models like preferential sorption-capillary flow model [2], Solution Diffusion model [3], Irreversible Thermodynamic model (Kedem-Katchalsky model [4] and Spiegler-Kedem model [5]), and Langmuir-type model [6] have been used for neutral membranes. In the case of charged membranes, the Nernst-Planck equation [7], electrostatic and steric hindrance model [8] have been used. Data driven models based on neural networks [9] have also been used to predict both permeate concentration and flux without solving any membrane transport equation.
Models proposed for charged membranes are developed by considering the chemical and physical properties of the solute and membrane such as solute size, solute charge, pore size of membrane and charge of membrane etc. On the other hand models based on the irreversible thermodynamics [4, 5] are developed by considering the membrane as a black box which has fluxes (permeate and solute flux) corresponding to the driving forces (pressure difference and concentration difference) of the transport process. The phenomenological constants are used to correlate flux and driving force, and physical parameters of the membrane are derived from these phenomenological constants. With irreversible thermodynamic models, the physical parameters of the membrane can be estimated for experimental data without knowing properties of membrane and solute. Soltanieh and Gill [10] compared the performance of the SK model and the KK model and observed that at no fouling condition, the membrane physical parameters of the KK model were found to be a function of feed concentration, while SK model parameters were found to be constant with respect to feed concentration. Several authors [11] compared the Solution Diffusion (SD) model with the SK model and concluded that the SK model predicts better than the SD model.
Murthy and Gupta. [12] proposed new a model, namely a Combined Film Spiegler-Kedem (CFSK) model, by including both membrane transport and concentration polarization effects. They concluded that CFSK model predictions are better than other models available in literature. Senthilmurugan et al [13] and Abhijit et al., [14] extended the CFSK model to spiral wound and hollow fiber modules respectively, and validated the models with experimental data with good results.